General
3D Pose Estimation in Projection Space via Pixel-level Visible Light Communication
arXiv cs.RO0 views
arXiv:2611.06121v1 Announce Type: new Abstract: Projector-based augmented reality enables natural interaction between users and devices by overlaying digital information onto the physical world through projected imagery. A key technical requirement of such systems is accurate positional alignment between the projector and the devices. Pixel-level Visible Light Communication (PVLC) achieves this alignment without external sensing infrastructure by embedding invisible spatial codes into each projected pixel through high-speed brightness modulation that preserves image quality. However, the information that PVLC transmits is inherently planar. PVLC has therefore been limited to devices moving on a flat surface and cannot estimate the 3D pose of devices in three-dimensional space, such as aerial robots. To extend PVLC-based pose estimation to three dimensions, we formulate it as a Perspective-n-Point (PnP) problem. The 2D pixel positions that four coplanar photosensors on the device receive via PVLC serve as the image points, and their known 3D layout provides the object points. Experiments show that the proposed system estimates 3D pose with a latency of approximately 8~ms and a 3D position RMSE of 19.2~mm after Kalman filtering. These results confirm the first realization of real-time 3D pose estimation coordinated with high-quality projected image content without external sensing infrastructure.
Source:https://arxiv.org/abs/2611.06121PreviousOnline Adaptation to Latent Physical Properties for Learning from DemonstrationNextA Layered View of LLM Support in Underwater Robotics
Related posts
Joint Association and Beamforming Design for Cooperative ISAC Systems
0arXiv eess.SP
Ambiguity Elimination via Successive Estimation in ISAC Systems with Reference Signals
0arXiv eess.SP
Community detection with the Bethe-Hessian
0arXiv stat.TH
Exact Transport-Information Correspondence for Distribution-Adaptive Discretization
0arXiv math.IT
Measuring the collaboration, not the agent
0arXiv cs.HC
Model Predictive Control of Heating Systems via Koopman-Operator Bilinearization
0arXiv eess.SY